Most Teams Are Using AI All Wrong

Recently I was scrolling LinkedIn when something caught my eye. I read a post, kept scrolling, then stopped and went back because I had that strange feeling of, “Didn’t I just read this?”

Turns out I had.

Two competitor companies I follow had posted nearly identical copy. Same message. Same structure. Even the same emojis placed in the same spots. It was one of those moments that is funny if you work in marketing and a little embarrassing if you imagine being the person who hit publish.

That was the moment I thought, this is exactly how people are using generative AI all wrong.

I have spent the past few years working at a tech startup in a highly competitive space, which means keeping a close eye on the market is not optional. I follow competitor companies, industry voices, and thought leaders because I like knowing what is actually happening, not just what people say is happening. Long before AI became part of everyday workflow, I had already built a competitor tracker in a spreadsheet. I used it to log things like new hires, customer logos, product announcements, trade shows, feature releases, and anything else that helped me spot patterns, momentum, and gaps.

At the time, I used to joke that a lot of our competitors were asleep at the wheel. They were barely active on social media. Very few were running digital ads. Virtual events were not really part of their strategy. So I became a hunter of information. I was working in a technical industry that helped power the internet, and yet many of the companies in it still seemed to rely on trade shows as the main way to generate leads and new business. That contrast was always fascinating to me.

What made that LinkedIn moment so interesting was not just that the posts were similar. It was that both companies were fighting for the attention of the same people, in the same industry, with the same audience in mind, and still no one had bothered to pause long enough to make the message their own.

That is what bad AI use looks like.

Someone clearly typed a lazy prompt into ChatGPT or another tool, asked it to write a post about a topic, copied the answer, and published it. No refinement. No strategy. No taste. No awareness that if everyone is using the same tools in the same way, the output is eventually going to collapse into sameness.

From a competitor standpoint, it was an LOL moment. But from the perspective of someone actually looking for a solution, it lands differently. If two companies sound interchangeable, they start to feel interchangeable. And that is not a great place to be when trust, differentiation, and first impressions matter.

The irony is that I am not anti-AI at all. I think AI can be incredibly useful, especially for lean teams, smaller companies, or anyone who needs a second brain to help them move faster. But using it as a copy-and-paste machine is one of the least interesting things it can do.

The better use is not just writing faster. It is seeing more clearly.

That old spreadsheet tracker I built is a good example. On its own, it was useful because it gave me a way to manually gather competitive signals in one place. But the real opportunity now is what AI can do once that information exists. Instead of simply collecting the data, you can use AI to analyze it, summarize it, identify patterns, flag changes, and turn scattered observations into something far more valuable.

You can have AI review a competitor tracker and surface things you might miss on your own. Which companies are increasing their event presence? Who is adding new functionality? Which competitors are expanding partnerships or integrations? Who seems to be investing more heavily in visibility? Which patterns suggest a shift in positioning or market focus?

That is where this gets interesting.

You could build a simple workflow where competitor updates are collected weekly, dropped into a spreadsheet or database, analyzed by AI, and then turned into a short report for stakeholders. Not a bloated deck no one reads. A useful summary of what changed, what matters, what is worth watching, and where opportunities may be opening up.

That is a much smarter use of AI than asking it to write a social post that ends up sounding like five other companies in your feed.

The same goes for internal decision-making. AI can help categorize messy market information, summarize patterns across spreadsheets, cluster recurring themes, compare feature sets, or even draft a weekly snapshot based on changes in competitor activity. It can help a team spend less time manually sorting information and more time deciding what to do with it.

That, to me, is the shortcut.

Not faster filler. Better intelligence.

Yes, AI can help with content. Yes, it can help you move faster. But if all you are doing is using it to generate polished posts and generic captions, you are using one of the most powerful tools available to you for one of the weakest possible outcomes.

The real opportunity is not just avoiding sameness. It is using AI to become more informed, more observant, and more strategic.

Because when everyone else is asking AI to write the post, the smarter move may be asking it to tell you what everyone else is missing.

If you already track competitor activity in a spreadsheet, Airtable, Notion, or even a running document, AI can help you turn that information into something far more useful than a static list of updates.

Want more practical shortcuts like this?
Explore my curated library of AI tools, prompts, and workflows at resources.taneilcurrie.com